Identifying transcriptional enhancers?the non-coding regulatory sequences required for regulating gene expression?is critical both for understanding the basic biology of disease vectors and especially for developing biotechnological means of manipulating their life cycles for their management and control. However, few such regulatory sequences have been identified for vector insects, including the major malaria vector Anopheles gambiae, despite the availability of completely sequenced genomes. The investigators have developed methods for effective computational enhancer discovery in Drosophila and have demonstrated that Drosophila enhancer data, which are extensive, can be leveraged to enable enhancer discovery in other insects as diverse as mosquitoes, beetles, bees, and wasps. The objective of this R21 application is to use this approach to discover and validate in vivo enhancers relevant to vector biology and insect biocontrol in the malaria mosquito An. gambiae. The rationale for this is that identification of cis-regulatory sequences has provided important advances in the study and control of mosquito disease vectors, but a much deeper collection of mosquito enhancers is needed. The proposed research has the potential to provide large numbers of known or predicted enhancers where few or none now exist. It is an exploratory, novel study that will break new ground in the field of mosquito genomics and genetics and is therefore ideally suited for the R21 grant mechanism. There are two specific aims: (1) Generate high-confidence enhancer predictions for An. gambiae; and (2) Validate the enhancer predictions in transgenic mosquitoes. This approach is innovative as it leverages the wealth of existing Drosophila cis-regulatory data to effectively predict enhancers over large evolutionary distances in an important vector species for which there is genome sequence but little functional data. The proposed research is significant because there is currently no other method available for rapid, efficient, and cost-effective enhancer discovery in already-sequenced, important vector species. If successful, it will demonstrate an ability to annotate the regulatory genomes of all insect disease vectors as they become sequenced without requiring extensive new genome-scale experimental data for each. These results will have an important positive impact through improved ability to understand and manipulate the biology of An. gambiae and other vector species to improve their management and control.